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Electromagnetic interference modeling and elimination for a solar/hydrogen hybrid powered small-scale UAV

  • Jiahao GE
  • , Li LIU*
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Contribution to journalArticlepeer-review

Abstract

The trajectory related and Direct Current (DC) Electromagnetic Interference (EMI) of lithium battery, fuel cell and photovoltaic modules has a great influence on the small-scale Unmanned Aerial Vehicle (UAV) airborne magnetometer and is hard to be shielded, calibrated or filtered. Besides, the mechanisms underlying the DC EMI have been rarely investigated yet. To cope with this problem, this paper systematically studies the EMI models, and proposes an online 3-layer EMI reduction scheme. First, EMI coupled with UAV motion model and hybrid power system is established. Second, the mechanism EMI models of hybrid power system are established and verified based on the proposed concept “equivalent current”. Third, an online 3-layer EMI reduction scheme is proposed, including battery layer, trajectory planning layer and energy management layer. In the first main layer, EMI self-cancellation is realized by rotating battery inclinations and symmetrical circuits. In response to errors, the trajectory planning layer reduces the EMI intensity by optimizing an optimal trajectory, while the energy management layer prioritizes power allocation to power sources that can produce small and stable EMI. Simulation results of climb, level flight and descent illustrate the efficaciousness and applicability of the proposed online 3-layer EMI reduction scheme.

Original languageEnglish
Pages (from-to)293-308
Number of pages16
JournalChinese Journal of Aeronautics
Volume36
Issue number10
DOIs
Publication statusPublished - Oct 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • EMI reduction
  • Electromagnetic interference
  • Energy management
  • Hybrid powered UAV
  • Mechanism modeling
  • Trajectory planning

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